DFKI-LT - Bootstrapping patterns for the detection of mobility related events
Bootstrapping patterns for the detection of mobility related events
3 14th Conference on Natural Language Processing, Vienna, Austria, Verlag der Österreichischen Akademie der Wissenschaften, 2018
This work presents a method to extract traffic events from German texts. We present a rule based system, where patterns are automatically extracted and ranked using a bootstrapping approach. These patterns are subsequently evaluated and annotated by human annotators. The resulting pattern are evaluated on three different text sources (Tweets, traffic RSS feeds, and news articles) with different language styles. Through the use of three data sets we cannot only evaluate the usefulness of the approach in a single domain but also evaluate the domain portability of the proposed approach. We further perform an error analysis to identify problems of the current system.
Files: BibTeX, KONVENS_2018_paper_20.pdf